library(dplyr)
library(plotly)
# Access key token
Sys.setenv('MAPBOX_TOKEN' = 'pk.eyJ1IjoiYnJpbWEiLCJhIjoiY2ptYm5pbXZ6MDd1czNwcW10OHN4Y2theSJ9.SNmXpvkIL14Wn1ebhRr_ug')
aegypti %>%
select(VECTOR, Y, X, YEAR, COUNTRY) %>% # selecting variables
filter(YEAR == 2004) %>% # filter by year
plot_mapbox(x = ~X, y =~Y, split = ~VECTOR, mode = "scattermapbox", hoverinfo = "name" ) %>% # scattemapbox
layout( title = "Scatter plot of mosquitos 2004",
mapbox = list(style = "light"),
margin = list(r = 25, l = 25, b = 25, t = 25, pad = 0.5)
)
# 2013 scatter plot of mosquitos
aegypti %>%
select(VECTOR, Y, X, YEAR, COUNTRY) %>%
filter(YEAR == 2013) %>%
plot_mapbox(x = ~X, y =~Y, split = ~VECTOR, mode = "scattermapbox", hoverinfo = "name" ) %>%
layout( title = "Scatter plot of mosquitos 2004",
mapbox = list(style = "light"),
margin = list(r = 25, l = 25, b = 25, t = 25, pad = 0.5)
)
# compute z (no. of mosquitos detected per country); choropleth
aegypti %>%
group_by(COUNTRY) %>%
mutate(Z = n()) %>%
plot_geo() %>%
add_trace(
z =~Z, name = 'Mosquito (Z)', color =~Z, color = "reds",
locations =~COUNTRY_ID
) %>%
layout(
title = "Number of mosquitos detected per country",
geo = list(
projection = list(type = "equirectangular")
)
)
aegypti %>%
group_by(COUNTRY) %>%
mutate(Z = log(n())) %>%
plot_geo() %>%
add_trace(
z =~Z, name = 'Mosquito (Z)', color =~Z, color = "reds",
locations =~COUNTRY_ID
) %>%
layout(
title = "Number of mosquitos detected per country",
geo = list(
projection = list(type = "equirectangular")
)
)
aegypti %>%
group_by(COUNTRY) %>%
mutate(Z = log(n())) %>%
plot_geo() %>%
add_trace(
z =~Z, name = 'Mosquito (Z)', color =~Z, color = "reds",
locations =~COUNTRY_ID
) %>%
layout(
title = "Number of mosquitos detected per country",
geo = list(projection = list(type = "conic equal area"))
)
d <- aegypti %>%
select(VECTOR, Y, X, YEAR, COUNTRY) %>%
filter(YEAR == 2013., COUNTRY == "Brazil") %>%
mutate(X1 = cut_interval(X, 100)) %>%
mutate(Y1 = cut_interval(Y, 100)) %>%
group_by(X1) %>%
mutate(mx = mean(X)) %>%
mutate(nx = n()) %>%
group_by(Y1) %>%
mutate(my = mean(Y)) %>%
mutate(ny = n()) %>%
mutate(N = ny + nx) %>%
group_by(X1, Y1) %>%
mutate(N2 = n()) %>%
group_by(X, Y) %>%
mutate(mean(X,Y))
d2 <- aegypti %>%
select(VECTOR, Y, X, YEAR, COUNTRY) %>%
filter(YEAR == 2013., COUNTRY == "Brazil") %>%
mutate(X1 = cut_interval(X, 100)) %>%
mutate(Y1 = cut_interval(Y, 100)) %>%
group_by(X1,Y1) %>%
summarise(mx = mean(X), my =mean(Y), N = n())
d2 %>%
plot_mapbox( mode = "scattermapbox", hoverinfo = "name") %>%
add_markers(x = ~mx, y = ~my, split =~N,size = ~N) %>%
layout( title = "Scatter plot of mosquitos 2013",
mapbox = list(style = "light"),
margin = list(r = 25, l = 25, b = 25, t = 25, pad = 0.5)
)